entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
Embedder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.nn
import torch.optim
assert_size_stride = tor... | BerenLuthien/ReAgent | Embedder | false | 13,384 | [
"BSD-3-Clause"
] | 1,156 | 52f666670a7fa03206812ef48949f6b934d400f7 | https://github.com/BerenLuthien/ReAgent/tree/52f666670a7fa03206812ef48949f6b934d400f7 |
GrayscaleLayer | import torch
import torch.nn as nn
class GrayscaleLayer(nn.Module):
def __init__(self):
super(GrayscaleLayer, self).__init__()
def forward(self, x):
return torch.mean(x, 1, keepdim=True)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | GuYuanjie/DeepFusionPrior | GrayscaleLayer | false | 5,229 | [
"MIT"
] | 1 | a7126e073ed8c49b6a9a662492b64aaeee56cc01 | https://github.com/GuYuanjie/DeepFusionPrior/tree/a7126e073ed8c49b6a9a662492b64aaeee56cc01 |
InceptionA | import torch
import torch.nn.functional as F
class InceptionA(torch.nn.Module):
def __init__(self, in_channels):
super(InceptionA, self).__init__()
self.branch1x1 = torch.nn.Conv2d(in_channels, 16, kernel_size=(1, 1))
self.branch_pool = torch.nn.Conv2d(in_channels, 24, kernel_size=(1, 1))... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | StarsStation/DeepLearning | InceptionA | false | 5,869 | [
"MIT"
] | 1 | a4c833af93652069f19a8c6f0b1e42cde64bbb79 | https://github.com/StarsStation/DeepLearning/tree/a4c833af93652069f19a8c6f0b1e42cde64bbb79 |
GluMlp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | SimonCqk/towhee | GluMlp | false | 9,632 | [
"Apache-2.0"
] | 0 | a187833b1411216106a80a71e6f2c6e68e1be330 | https://github.com/SimonCqk/towhee/tree/a187833b1411216106a80a71e6f2c6e68e1be330 |
generator | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | trisct/BSP-NET-pytorch | generator | false | 13,048 | [
"MIT"
] | 0 | 31f148aa3d7321bac854bc3de6c88f676236b7e4 | https://github.com/trisct/BSP-NET-pytorch/tree/31f148aa3d7321bac854bc3de6c88f676236b7e4 |
NetVLAD | import torch
import torch.nn as nn
import torch.nn.functional as F
class NetVLAD(nn.Module):
"""NetVLAD layer implementation"""
def __init__(self, num_clusters=64, dim=128, alpha=100.0,
normalize_input=True):
"""
Args:
num_clusters : int
The number of clust... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Shubodh/NetVLAD-pytorch | NetVLAD | false | 9,510 | [
"MIT"
] | 0 | ea45bac16dbb3e3bec4172df58715bf3526ee502 | https://github.com/Shubodh/NetVLAD-pytorch/tree/ea45bac16dbb3e3bec4172df58715bf3526ee502 |
SpatialAttentionModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | OrKatz7/kaggle-hubmap | SpatialAttentionModule | false | 9,886 | [
"MIT"
] | 0 | 5cf8c5aebe956c256fa7f3db432639e28f29c6a3 | https://github.com/OrKatz7/kaggle-hubmap/tree/5cf8c5aebe956c256fa7f3db432639e28f29c6a3 |
BinaryTreeComposer | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.onnx
class BinaryTreeComposer(nn.Module):
"""
local lc, lh = nn.Identity()(), nn.Identity()()
local rc, rh = nn.Identity()(), nn.Identity()()
local new_gate = function()
return nn.CAddTable(){
nn.Linear(self.mem_dim, s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | supunab/Lantern | BinaryTreeComposer | false | 16,520 | [
"BSD-3-Clause"
] | 158 | 932a031816617d71c46653f3b2245129a6a8a7c8 | https://github.com/supunab/Lantern/tree/932a031816617d71c46653f3b2245129a6a8a7c8 |
PoolingF | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
impo... | guyii54/Contrastive-I2I | PoolingF | false | 6,779 | [
"BSD-3-Clause"
] | 1 | e73daa0f9d3770c2280a304c39678d5b22440647 | https://github.com/guyii54/Contrastive-I2I/tree/e73daa0f9d3770c2280a304c39678d5b22440647 |
MIRB1 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | wwjfsfs/wwjyyds | MIRB1 | false | 13,210 | [
"MIT"
] | 0 | 80cd6267fde7cd98838078a0d5178a557ceb7414 | https://github.com/wwjfsfs/wwjyyds/tree/80cd6267fde7cd98838078a0d5178a557ceb7414 |
Critic | import torch
import torch.nn as nn
class Critic(nn.Module):
def __init__(self, hidden_size, action, num_inputs, spp_num_outputs,
data_width=8):
super(Critic, self).__init__()
self.action = action
self.num_outputs = self.action.shape[0]
self.num_inputs = num_inputs
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | GraceYYJ/cbx-k | Critic | false | 9,079 | [
"MIT"
] | 0 | 1a955bc8d1675b8024763218482372dca982cc6c | https://github.com/GraceYYJ/cbx-k/tree/1a955bc8d1675b8024763218482372dca982cc6c |
UpConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | kkrish39/realtime-depth-prediction-from-monocular-videos | UpConv | false | 7,042 | [
"BSD-3-Clause"
] | 1 | 9cde9c1a6df6c91af1ada80b3aaeebae03fc59dc | https://github.com/kkrish39/realtime-depth-prediction-from-monocular-videos/tree/9cde9c1a6df6c91af1ada80b3aaeebae03fc59dc |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
def __init__(self, size_average=True, ignore_index=-100, reduce=True):
super(DiceLoss, self).__init__()
self.size_average = size_average
self.ignore_index = ignore_index
self.reduce = reduce
self.softMax = nn.So... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | GTreeSoftware/DB-Enhance | DiceLoss | false | 2,287 | [
"MIT"
] | 0 | 98332c62297db7756f5385c038089bb8736a27c0 | https://github.com/GTreeSoftware/DB-Enhance/tree/98332c62297db7756f5385c038089bb8736a27c0 |
ConvNetsModel | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvNetsModel(nn.Module):
def __init__(self, num_classes, cross_entropy_loss=False, kernel_size=3,
channel_size1=32, channel_size2=64, dropout=False):
super(ConvNetsModel, self).__init__()
self.cross_entropy_loss = c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | LidiaAlecci/ConvNet | ConvNetsModel | false | 11,664 | [
"MIT"
] | 0 | 23bc0919edfa346440588f79bc86d9c5f5fcc4d2 | https://github.com/LidiaAlecci/ConvNet/tree/23bc0919edfa346440588f79bc86d9c5f5fcc4d2 |
LayerELU | import random
import torch
import torch.nn as nn
class LayerELU(nn.Module):
"""
Test for nn.layers based types
"""
def __init__(self):
super(LayerELU, self).__init__()
self.alpha = random.random()
self.elu = nn.ELU(alpha=self.alpha)
def forward(self, x):
x = self.... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import random
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guard... | dawnclaude/onnx2keras | LayerELU | false | 15,153 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
MaxPool2d | import torch
import torch.nn as nn
class MaxPool2d(nn.Module):
def __init__(self):
super(MaxPool2d, self).__init__()
self.layer = nn.MaxPool2d(3, stride=2)
def forward(self, x):
x = self.layer(x)
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_ini... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | yifanpu001/PytorchToCaffe | MaxPool2d | false | 4,717 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
FeatureExtractFF | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | criteo-research/pytorch-ada | FeatureExtractFF | false | 15,082 | [
"Apache-2.0"
] | 68 | 4b8861ce1c12fc8a4391eb14a811459e3e8a074a | https://github.com/criteo-research/pytorch-ada/tree/4b8861ce1c12fc8a4391eb14a811459e3e8a074a |
Symmetric | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import to... | MartinRenaudin/tutorials | Symmetric | false | 2,762 | [
"BSD-3-Clause"
] | 0 | 035d6827d77c52fed2a927f105e39fd73516f093 | https://github.com/MartinRenaudin/tutorials/tree/035d6827d77c52fed2a927f105e39fd73516f093 |
h_sigmoid | import torch
import torch.nn as nn
class h_sigmoid(nn.Module):
def __init__(self, inplace=True):
super(h_sigmoid, self).__init__()
self.relu = nn.ReLU6(inplace=inplace)
def forward(self, x):
return self.relu(x + 3) / 6
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def g... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Felicia980317/mytorch | h_sigmoid | false | 443 | [
"Apache-2.0"
] | 0 | e463122c0d402878ec5b4c5a823a0feeba8fdbfe | https://github.com/Felicia980317/mytorch/tree/e463122c0d402878ec5b4c5a823a0feeba8fdbfe |
SmallConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from numpy import prod
assert_size_stride = torch._C._dyna... | Jennifer-Rigdon/fvcore | SmallConvNet | false | 5,391 | [
"Apache-2.0"
] | 1 | 7e800a86f2df93da017e07380543b4060ab88c94 | https://github.com/Jennifer-Rigdon/fvcore/tree/7e800a86f2df93da017e07380543b4060ab88c94 |
EqualLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | naarkhoo/GFPGAN | EqualLinear | false | 10,565 | [
"BSD-3-Clause"
] | 0 | 73559ec44a734fe084b6a0e28107295c5e98f335 | https://github.com/naarkhoo/GFPGAN/tree/73559ec44a734fe084b6a0e28107295c5e98f335 |
GLU | import torch
import torch.nn as nn
from torch.nn.utils.rnn import *
import torch.nn.parallel
import torch.nn.functional as F
class GLU(nn.Module):
def __init__(self):
super(GLU, self).__init__()
def forward(self, x):
nc = x.size(1)
assert nc % 2 == 0, 'channels dont divide 2!'
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn.utils.rnn import *
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | ArunKodnani/StackGAN-v2 | GLU | false | 8,850 | [
"MIT"
] | 0 | e2ef678049b2e18b4a076cecfbe220cf270e59e6 | https://github.com/ArunKodnani/StackGAN-v2/tree/e2ef678049b2e18b4a076cecfbe220cf270e59e6 |
CosineSimilarity | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | IBM/aihn-ucsd | CosineSimilarity | false | 8,255 | [
"Apache-2.0"
] | 20 | 6c6a56d11c704b529a31868418e350e9760ff9d9 | https://github.com/IBM/aihn-ucsd/tree/6c6a56d11c704b529a31868418e350e9760ff9d9 |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class BertSelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
'The hidden size (%... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Sologa/awesome-align | BertSelfAttention | false | 14,433 | [
"BSD-3-Clause"
] | 173 | 62eaae7eac9bac06c10627fac6cc942c07a50e64 | https://github.com/Sologa/awesome-align/tree/62eaae7eac9bac06c10627fac6cc942c07a50e64 |
PlainRefiner | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | akimotty877/mmediting | PlainRefiner | false | 3,071 | [
"Apache-2.0"
] | 0 | cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 | https://github.com/akimotty877/mmediting/tree/cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 |
SimpleNotModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | YaronBenAtar/glow | SimpleNotModule | false | 14,657 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
ResBlock | import torch
import torch.nn as nn
class ResBlock(nn.Module):
def __init__(self, in_ch, hid_ch):
super(ResBlock, self).__init__()
self.act = nn.ReLU()
self.conv1 = nn.Conv2d(in_ch, hid_ch, kernel_size=3, padding=1)
self.conv2 = nn.Conv2d(hid_ch, hid_ch, kernel_size=3, padding=1)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | qbhan/pathembed | ResBlock | false | 7,508 | [
"MIT"
] | 1 | c21823529840593bf606e10696f5879e5adb51b2 | https://github.com/qbhan/pathembed/tree/c21823529840593bf606e10696f5879e5adb51b2 |
TripletLogExpLoss | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
class TripletLogExpLoss(nn.Module):
"""Creates a criterion that measures the triplet loss given an input
tensors x1, x2, x3.
This is used for measuring a relative similarity between samples. A triplet
is composed by ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import numpy as np
import torch.nn as nn
assert_size_stride = ... | zhangxue123/deep-image-retrieval | TripletLogExpLoss | false | 13,170 | [
"BSD-3-Clause"
] | 0 | ac188856fa5a034aed3f7ed3fb617d580da44462 | https://github.com/zhangxue123/deep-image-retrieval/tree/ac188856fa5a034aed3f7ed3fb617d580da44462 |
ESA | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | hduba/KAIR | ESA | false | 3,600 | [
"MIT"
] | 0 | dbd7596c7e4a4667b9b7baac369fc6c02571fa58 | https://github.com/hduba/KAIR/tree/dbd7596c7e4a4667b9b7baac369fc6c02571fa58 |
ScaleNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_... | Azerrroth/spacetimeformer | ScaleNorm | false | 92 | [
"MIT"
] | 0 | e822444a6d696a1edb9e446d6f3482a70681be3c | https://github.com/Azerrroth/spacetimeformer/tree/e822444a6d696a1edb9e446d6f3482a70681be3c |
LayerNorm | import torch
from torch import nn
import torch.utils.data
class LayerNorm(nn.Module):
def __init__(self, channels, eps=0.0001):
super().__init__()
self.channels = channels
self.eps = eps
self.gamma = nn.Parameter(torch.ones(channels))
self.beta = nn.Parameter(torch.zeros(c... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | AndreHe02/glow-tts | LayerNorm | false | 1,948 | [
"MIT"
] | 0 | 683f68f17790f2f46c23e9d3eadbcac352d82e2b | https://github.com/AndreHe02/glow-tts/tree/683f68f17790f2f46c23e9d3eadbcac352d82e2b |
InnerProductLayer | import torch
import torch.nn as nn
from sklearn.metrics import *
import torch.onnx
import torch as torch
class InnerProductLayer(nn.Module):
"""InnerProduct Layer used in PNN that compute the element-wise
product or inner product between feature vectors.
Input shape
- a list of 3D tensor with sh... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from sklearn.metrics import *
import torch.onnx
import torch as torch
assert_size_stride = torch._C._dynamo.guards.ass... | dulvqingyunLT/DeepCTR-Torch | InnerProductLayer | false | 10,345 | [
"Apache-2.0"
] | 0 | f40cf08f3469aa471f9ca69e44c5de51180341cc | https://github.com/dulvqingyunLT/DeepCTR-Torch/tree/f40cf08f3469aa471f9ca69e44c5de51180341cc |
ProjectionLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import math
import tor... | RRemixx/DMRDenoise | ProjectionLoss | false | 14,287 | [
"MIT"
] | 79 | 026d25f9eaf98fdfd85a67caeb9b49cab71148e9 | https://github.com/RRemixx/DMRDenoise/tree/026d25f9eaf98fdfd85a67caeb9b49cab71148e9 |
ReSentenceMatrixLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Yottaxx/T-LSTM | ReSentenceMatrixLayer | false | 18,151 | [
"MIT"
] | 9 | 92618d8c3ee2418b194a2e1592512548da955b77 | https://github.com/Yottaxx/T-LSTM/tree/92618d8c3ee2418b194a2e1592512548da955b77 |
LeNet300 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from typing import *
import t... | chomd90/snip | LeNet300 | false | 1,702 | [
"MIT"
] | 0 | 04aa8ca76364c61c3f6013832827fa292402652b | https://github.com/chomd90/snip/tree/04aa8ca76364c61c3f6013832827fa292402652b |
DPGRUCell | import math
import torch
from torch import Tensor
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
from typing import Optional
class RNNLinear(nn.Linear):
"""Applies a linear transformation to the incoming data: :math:`y = xA^T + b`
This module is the same as a ``torch.nn.Line... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | bogdan-kulynych/opacus | DPGRUCell | false | 3,239 | [
"Apache-2.0"
] | 0 | e2d13003a179f64920835bc585f3729b8148279f | https://github.com/bogdan-kulynych/opacus/tree/e2d13003a179f64920835bc585f3729b8148279f |
LinearDiag | import torch
import torch.nn as nn
import torch.optim
import torch.nn.parallel
class LinearDiag(nn.Module):
def __init__(self, num_features, bias=False):
super(LinearDiag, self).__init__()
weight = torch.FloatTensor(num_features).fill_(1)
self.weight = nn.Parameter(weight, requires_grad=T... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.optim
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_stri... | Basasuya/FewShotWithoutForgetting | LinearDiag | false | 2,007 | [
"MIT"
] | 0 | eecc70e416ed82999124ddfca1b145f6dbcd74a6 | https://github.com/Basasuya/FewShotWithoutForgetting/tree/eecc70e416ed82999124ddfca1b145f6dbcd74a6 |
UpsampleConvLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | joaquingv12/Solving-Image-Processing-Problems-with-Python-Part1 | UpsampleConvLayer | false | 6,969 | [
"MIT"
] | 1 | 42512672d1dc660dabc2d4570e891315f5264b12 | https://github.com/joaquingv12/Solving-Image-Processing-Problems-with-Python-Part1/tree/42512672d1dc660dabc2d4570e891315f5264b12 |
MetricLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.jit
import torch.nn
assert_size_stride = torch._C._dyn... | ankmathur96/torchsupport | MetricLoss | false | 3,160 | [
"MIT"
] | 0 | 77bf4a90b8770a408665e2604428808c3ed2f979 | https://github.com/ankmathur96/torchsupport/tree/77bf4a90b8770a408665e2604428808c3ed2f979 |
Delta | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torchaudio import transforms
assert_size_stride = tor... | B06901052/s3prl | Delta | false | 154 | [
"MIT"
] | 0 | 5f63d2df043d2d7c81580cd042fa2cea34746f48 | https://github.com/B06901052/s3prl/tree/5f63d2df043d2d7c81580cd042fa2cea34746f48 |
TokenEmbedding | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import to... | Nayef211/tutorials | TokenEmbedding | false | 9,540 | [
"BSD-3-Clause"
] | 0 | faf2c476fc3be855051fbea3cce77eaf7b2a2175 | https://github.com/Nayef211/tutorials/tree/faf2c476fc3be855051fbea3cce77eaf7b2a2175 |
NormalizedLinear | import math
import torch
import torch.utils.data
from itertools import product as product
from math import sqrt as sqrt
import torch.nn
class NormalizedLinear(torch.nn.Module):
"""
A advanced Linear layer which supports weight normalization or cosine normalization.
"""
def __init__(self, in_features... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | tonysy/cvpods | NormalizedLinear | false | 16,607 | [
"Apache-2.0"
] | 548 | e322d7842ca0e34b1ef6237ea6d350633efc793a | https://github.com/tonysy/cvpods/tree/e322d7842ca0e34b1ef6237ea6d350633efc793a |
FinalPool | import torch
import torch.utils.data
class FinalPool(torch.nn.Module):
def __init__(self):
super(FinalPool, self).__init__()
def forward(self, input):
"""
input : Tensor of shape (batch size, T, Cin)
Outputs a Tensor of shape (batch size, Cin).
"""
return input.max(dim=1)[0]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
e... | CoraJung/end-to-end-spoken-language-understanding | FinalPool | false | 5,020 | [
"Apache-2.0"
] | 1 | d1b15dad1a8f01336bcb0adcbf95d8c6ea279d09 | https://github.com/CoraJung/end-to-end-spoken-language-understanding/tree/d1b15dad1a8f01336bcb0adcbf95d8c6ea279d09 |
SinkhornKnopp | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | DonkeyShot21/UNO | SinkhornKnopp | false | 13,639 | [
"MIT"
] | 87 | 7613d3f8c58e5f16ee0d68fdd803ef442d819af4 | https://github.com/DonkeyShot21/UNO/tree/7613d3f8c58e5f16ee0d68fdd803ef442d819af4 |
StdConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Willy0919/progressive-coordinate-transforms | StdConv2d | false | 14,591 | [
"Apache-2.0",
"MIT"
] | 142 | b637fa2541a815d270e162a4c9cd3348b098d48a | https://github.com/Willy0919/progressive-coordinate-transforms/tree/b637fa2541a815d270e162a4c9cd3348b098d48a |
ImageToTensor | import torch
import numpy as np
import torch.optim
import torch.nn as nn
import torch.nn.utils
import torch.autograd
class BaseMetric:
""" Base class for all the metrics """
def __init__(self, name):
self.name = name
def calculate(self, batch_info):
""" Calculate value of a metric based ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.optim
import torch.nn as nn
import torch.nn.utils
import torch.autograd
assert_size_stride = torch._C._dynam... | galatolofederico/vel | ImageToTensor | false | 15,395 | [
"MIT"
] | 273 | 0473648cffb3f34fb784d12dbb25844ab58ffc3c | https://github.com/galatolofederico/vel/tree/0473648cffb3f34fb784d12dbb25844ab58ffc3c |
BasicBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
"""
BasicBlock implementation for ResNet
reference: https://github.com/kuangliu/pytorch-cifar/blob/master/models/resnet.py
"""
expansion = 1
def __init__(self, device, in_planes, planes, strid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | EgonFerri/Final_project_Aml_ARC | BasicBlock | false | 2,188 | [
"MIT"
] | 0 | d5290a0bfef5e1aa0feb5988cdfe6de704180485 | https://github.com/EgonFerri/Final_project_Aml_ARC/tree/d5290a0bfef5e1aa0feb5988cdfe6de704180485 |
ExtractTensorPatches | import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Tuple
from typing import Union
from typing import Optional
from torch.nn.modules.utils import _pair
def _extract_tensor_patchesnd(input: 'torch.Tensor', window_sizes:
'Tuple[int, ...]', strides: 'Tuple[int, ...]') ->torch.Tensor... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
from typing import Tuple
from typing import Union
from typing import Optional
from tor... | ChristophReich1996/kornia | ExtractTensorPatches | false | 276 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 35f955b46e8015da1cb9faa28c6943ec2b09cc2a | https://github.com/ChristophReich1996/kornia/tree/35f955b46e8015da1cb9faa28c6943ec2b09cc2a |
ContrastiveLoss | import torch
class ContrastiveLoss(torch.nn.Module):
"""
Contrastive loss function.
Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
"""
def __init__(self, margin=2.0):
super(ContrastiveLoss, self).__init__()
self.margin = margin
def forward(self, d... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | VictorCallejas/FB-Similarity-Challenge | ContrastiveLoss | false | 2,928 | [
"MIT"
] | 0 | 0092071f29d5d8fab055d27a1e542e2e64e9cdab | https://github.com/VictorCallejas/FB-Similarity-Challenge/tree/0092071f29d5d8fab055d27a1e542e2e64e9cdab |
maxpool | import torch
import torch.nn as nn
class maxpool(nn.Module):
def __init__(self, layer=10, channels=32):
super(maxpool, self).__init__()
layers = []
for i in range(layer):
layers.append(nn.MaxPool2d(3, 1, 1))
self.layers = nn.Sequential(*layers)
def forward(self, x... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | yifanpu001/PytorchToCaffe | maxpool | false | 4,724 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
architecture | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self):
super(Decoder, self).__init__()
self.layers = nn.Sequential()
self.layers.add_module('Conv3', nn.Conv2d(64, 32, 3, 1, 1))
self.layers.add_module('Act3', nn.ReLU(inplace=True))
self.layers.add_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | VarunBabbar/Image_Compressor | architecture | false | 1,188 | [
"MIT"
] | 0 | 254d8d411f7cd16f3ce242275532c9fca537269c | https://github.com/VarunBabbar/Image_Compressor/tree/254d8d411f7cd16f3ce242275532c9fca537269c |
Net1 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | ringier-data/deep-learning-containers | Net1 | false | 7,547 | [
"Apache-2.0"
] | 1 | e939ceee48a426f9ae4e0b50317dc2fa8845a312 | https://github.com/ringier-data/deep-learning-containers/tree/e939ceee48a426f9ae4e0b50317dc2fa8845a312 |
GumbelSoftMax | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_ma... | MinliangLin/lightDSFD | GumbelSoftMax | false | 14,034 | [
"MIT"
] | 87 | 5f04ab89ac08eaf69d16c96f6c9e237701f80281 | https://github.com/MinliangLin/lightDSFD/tree/5f04ab89ac08eaf69d16c96f6c9e237701f80281 |
Conv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
import math
from torch.nn import functional as F
imp... | Dora-The-Kid/culture_network | Conv2d | false | 2,166 | [
"Apache-2.0"
] | 0 | bc2bac86e821faa797eeb2670d179395724f7922 | https://github.com/Dora-The-Kid/culture_network/tree/bc2bac86e821faa797eeb2670d179395724f7922 |
TransformerLayer | import torch
from torch import nn
from typing import Optional
class TransformerLayer(nn.Module):
"""TransformerEncoderLayer is made up of self-attn and feedforward network.
This standard encoder layer is based on the paper "Attention Is All You Need".
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszko... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | rgreenblatt/path | TransformerLayer | false | 7,575 | [
"MIT"
] | 1 | 2057618ee3a6067c230c1c1c40856d2c9f5006b0 | https://github.com/rgreenblatt/path/tree/2057618ee3a6067c230c1c1c40856d2c9f5006b0 |
StyleBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | Aarsh2001/annotated_deep_learning_paper_implementations | StyleBlock | false | 4,809 | [
"MIT"
] | 1 | ff0d5c065da1a46769f5f66fddc252c178f8fa37 | https://github.com/Aarsh2001/annotated_deep_learning_paper_implementations/tree/ff0d5c065da1a46769f5f66fddc252c178f8fa37 |
PositionEmbedding | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | choumartin1234/Music-Eye | PositionEmbedding | false | 6,438 | [
"MIT"
] | 1 | 059b43fd21f7e7bf6c84cb35a03fd936e64b59a5 | https://github.com/choumartin1234/Music-Eye/tree/059b43fd21f7e7bf6c84cb35a03fd936e64b59a5 |
DistanceNetwork | import torch
import torch.nn as nn
import torch.utils.checkpoint
class DistanceNetwork(nn.Module):
def __init__(self, n_feat, p_drop=0.1):
super(DistanceNetwork, self).__init__()
self.proj_symm = nn.Linear(n_feat, 37 * 2)
self.proj_asymm = nn.Linear(n_feat, 37 + 19)
self.reset_par... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.checkpoint
assert_size_stride = torch._... | RosettaCommons/RFDesign | DistanceNetwork | false | 14,328 | [
"MIT"
] | 45 | b404b8b2c57f89c047529c30259aeeb8f6012b61 | https://github.com/RosettaCommons/RFDesign/tree/b404b8b2c57f89c047529c30259aeeb8f6012b61 |
ScaledDotProductAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | connoisseures/vedastr | ScaledDotProductAttention | false | 10,029 | [
"Apache-2.0"
] | 0 | 5dc64f3f6f810f615414aec3508e5dfba1239216 | https://github.com/connoisseures/vedastr/tree/5dc64f3f6f810f615414aec3508e5dfba1239216 |
LipNormConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
def _max_except_dim(input, dim):
maxed = input
for axis in range(input.ndimension() - 1, dim, -1):
maxed, _ = maxed.max(axis, keepdim=True)
for axis in range(dim - 1, -1, -1):
maxed, _ = maxed.max(axis, keepdim=True)
re... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | hologerry/residual-flows | LipNormConv2d | false | 10,305 | [
"MIT"
] | 0 | 33a3639150490279c2e13238dd6244b80c52adf7 | https://github.com/hologerry/residual-flows/tree/33a3639150490279c2e13238dd6244b80c52adf7 |
RelationCrossing | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | BUPT-GAMMA/OpenHGNN | RelationCrossing | false | 13,367 | [
"Apache-2.0"
] | 235 | 5f218dad4ed1415aa6d842bc20785c61e74e5405 | https://github.com/BUPT-GAMMA/OpenHGNN/tree/5f218dad4ed1415aa6d842bc20785c61e74e5405 |
GramMatrix | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | bigsshark/mycode | GramMatrix | false | 9,787 | [
"MIT"
] | 0 | 550e58675cd533265b6a21258aa7bc1859191011 | https://github.com/bigsshark/mycode/tree/550e58675cd533265b6a21258aa7bc1859191011 |
Aggregator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | tilacyn/dsb2018_topcoders | Aggregator | false | 16,593 | [
"MIT"
] | 413 | e0f95ef70bc062d4dea321d2aa73231a9538cd63 | https://github.com/tilacyn/dsb2018_topcoders/tree/e0f95ef70bc062d4dea321d2aa73231a9538cd63 |
HLCriterion | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | anlewy/mt-dnn | HLCriterion | false | 14,864 | [
"MIT"
] | 2,075 | eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 | https://github.com/anlewy/mt-dnn/tree/eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 |
AGRUCell | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Fanxingye/DeepRS | AGRUCell | false | 14,027 | [
"Apache-2.0"
] | 1,770 | 06b98cf2cb2781656805eafc577fbd088f37d17d | https://github.com/Fanxingye/DeepRS/tree/06b98cf2cb2781656805eafc577fbd088f37d17d |
DummyMCObjective | from torch.nn import Module
import torch
from torch import Tensor
from abc import ABC
from abc import abstractmethod
class AcquisitionObjective(Module, ABC):
"""Abstract base class for objectives."""
...
class MCAcquisitionObjective(AcquisitionObjective):
"""Abstract base class for MC-based objectives."... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import Tensor
from abc import ABC
from abc import abstractmethod
assert_size_stride = torch._C._dynam... | jmren168/botorch | DummyMCObjective | false | 6,960 | [
"MIT"
] | 1 | 6c067185f56d3a244c4093393b8a97388fb1c0b3 | https://github.com/jmren168/botorch/tree/6c067185f56d3a244c4093393b8a97388fb1c0b3 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Nicolik/SimpleCNNClassifier | Net | false | 8,618 | [
"MIT"
] | 11 | e5cd37fbde90f4096183658abe3f8836be92a8f2 | https://github.com/Nicolik/SimpleCNNClassifier/tree/e5cd37fbde90f4096183658abe3f8836be92a8f2 |
Length | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | clementpoiret/3D-AGSCaps | Length | false | 6,449 | [
"MIT"
] | 1 | 475eb1915bc1425cebbd0bec36e9096c9c2cb53c | https://github.com/clementpoiret/3D-AGSCaps/tree/475eb1915bc1425cebbd0bec36e9096c9c2cb53c |
Attention | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import *
class Attention(nn.Module):
def __init__(self, opt):
super(Attention, self).__init__()
self.rnn_size = opt.rnn_size
self.att_hid_size = opt.att_hid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | YinTaiChen/NeuralBabyTalk | Attention | false | 14,693 | [
"MIT"
] | 554 | 2915ca702657866dc5b6b44614d0f6333c72bd3b | https://github.com/YinTaiChen/NeuralBabyTalk/tree/2915ca702657866dc5b6b44614d0f6333c72bd3b |
LogSTFTMagnitude | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class LogSTFTMagnitude(nn.Module):
def __init__(self):
super().__init__()
def forward(self, predicts_mag, targets_mag):
log_predicts_mag = torch.log(predicts_mag)
log_targets_mag = torch.log(ta... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | SolomidHero/speech-regeneration-enhancer | LogSTFTMagnitude | false | 17,948 | [
"MIT"
] | 8 | eb43907ff085d68a707ff7bc3af14e93ff66fd65 | https://github.com/SolomidHero/speech-regeneration-enhancer/tree/eb43907ff085d68a707ff7bc3af14e93ff66fd65 |
SEBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn.parallel
impo... | Desmond-97/RepVGG | SEBlock | false | 9,024 | [
"MIT"
] | 0 | 147490c54ee7b83d4a432a5913b17c8800e55d06 | https://github.com/Desmond-97/RepVGG/tree/147490c54ee7b83d4a432a5913b17c8800e55d06 |
SelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | dogeplusplus/sandbox | SelfAttention | false | 1,864 | [
"MIT"
] | 0 | c9041c06da9454f6c3cec622abbbf918c9f13bdc | https://github.com/dogeplusplus/sandbox/tree/c9041c06da9454f6c3cec622abbbf918c9f13bdc |
LogSumExpPool | import torch
from torch import nn
class LogSumExpPool(nn.Module):
def __init__(self, gamma):
super(LogSumExpPool, self).__init__()
self.gamma = gamma
def forward(self, feat_map):
"""
Numerically stable implementation of the operation
Arguments:
feat_map(Te... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | alinstein/X_RAY | LogSumExpPool | false | 18,259 | [
"MIT"
] | 4 | 35a39761d3b11ce9e47509025054f25e5f26aab9 | https://github.com/alinstein/X_RAY/tree/35a39761d3b11ce9e47509025054f25e5f26aab9 |
Prototype | import torch
import torch.nn
import torch.optim
import torch.utils.data
class Prototype(torch.nn.Module):
""""""
def __init__(self, prototype_num, latent_size) ->None:
super(Prototype, self).__init__()
self.latent_size = latent_size
self.prototype_num = prototype_num
self.prot... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | wenqiangxie/Prototype-Net | Prototype | false | 4,528 | [
"MIT"
] | 0 | a5ddd9976b78828d87806f9451a5092de3ff5c69 | https://github.com/wenqiangxie/Prototype-Net/tree/a5ddd9976b78828d87806f9451a5092de3ff5c69 |
MaxPoolingAggregator_1 | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from dataclasses import dataclass
from collections import defaultdict
import torch.optim
... | lavis-nlp/irtm | MaxPoolingAggregator_1 | false | 10,409 | [
"MIT"
] | 0 | e6c96519918795cfaa0c09ef2d4164f451265518 | https://github.com/lavis-nlp/irtm/tree/e6c96519918795cfaa0c09ef2d4164f451265518 |
InfoLoss | import math
import torch
from torch import nn
import torch.utils.data
class InfoLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, eps=1e-08):
x = torch.mean(x, 0)
logN = math.log(float(x.shape[0]))
x = x * (x + eps).log() / logN
neg_entropy ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
import torch.utils.data
assert_size_stride = torch._... | Joshua-Schroijen/deepproblog | InfoLoss | false | 670 | [
"Apache-2.0"
] | 0 | 4ae56f1e860010b7857b29d5bd76fb1555d5e19d | https://github.com/Joshua-Schroijen/deepproblog/tree/4ae56f1e860010b7857b29d5bd76fb1555d5e19d |
Exp | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | Praneethsv/prob_mbrl | Exp | false | 14,230 | [
"MIT"
] | 108 | 7b1adee6bff742b6f90e9b96ea243f12c9153b9b | https://github.com/Praneethsv/prob_mbrl/tree/7b1adee6bff742b6f90e9b96ea243f12c9153b9b |
Block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | sparseinference/argmaxnet | Block | false | 10,800 | [
"MIT"
] | 0 | ff1e090a662d384f2ba4349494c9630079d2545b | https://github.com/sparseinference/argmaxnet/tree/ff1e090a662d384f2ba4349494c9630079d2545b |
NaiveGroupNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn import Module
from torch.nn import Parameter
from torch.nn import... | Tanveer81/BoxVOS | NaiveGroupNorm | false | 17,982 | [
"BSD-2-Clause"
] | 4 | c30aa319f18f3fbee2a25e0ed25cb006a4598300 | https://github.com/Tanveer81/BoxVOS/tree/c30aa319f18f3fbee2a25e0ed25cb006a4598300 |
CrossEntropyLoss | import torch
import torch.utils.cpp_extension
class CrossEntropyLoss(torch.nn.Module):
def __init__(self):
super(CrossEntropyLoss, self).__init__()
self.ce_loss = torch.nn.CrossEntropyLoss()
def forward(self, cls_output, label, **_):
return self.ce_loss(cls_output, label).mean()
de... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.cpp... | yingnengd/MyGAN | CrossEntropyLoss | false | 4,741 | [
"MIT"
] | 0 | 6e4abbe165c8f3b1e1b69d5d01177712761a3a1c | https://github.com/yingnengd/MyGAN/tree/6e4abbe165c8f3b1e1b69d5d01177712761a3a1c |
BCEBlurWithLogitsLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Aditya239233/MDP | BCEBlurWithLogitsLoss | false | 16,902 | [
"MIT"
] | 4 | 87491e1d67e547c11f4bdd5d784d120473429eae | https://github.com/Aditya239233/MDP/tree/87491e1d67e547c11f4bdd5d784d120473429eae |
DiceLoss | import torch
from torch import nn
import torch.hub
def soft_dice_loss(outputs, targets, per_image=False, reduce=True, ohpm=
False, ohpm_pixels=256 * 256):
batch_size = outputs.size()[0]
eps = 0.001
if not per_image:
batch_size = 1
if ohpm:
dice_target = targets.contiguous().view(-1... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.hub
assert_size_stride = torch._C._dynamo.guards.assert... | selimsef/xview2_solution | DiceLoss | false | 16,378 | [
"Apache-2.0"
] | 57 | 5d0caba9c7a9c2707565a189f1a091c86d26b546 | https://github.com/selimsef/xview2_solution/tree/5d0caba9c7a9c2707565a189f1a091c86d26b546 |
LinearRegression | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | JohnlNguyen/FLSim | LinearRegression | false | 13,906 | [
"BSD-3-Clause"
] | 79 | a5ed7c0b84499cd9dbc5fe95f8bcb4ba8ab5a5cb | https://github.com/JohnlNguyen/FLSim/tree/a5ed7c0b84499cd9dbc5fe95f8bcb4ba8ab5a5cb |
ContrastiveLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
impo... | MinesNicaicai/large-scale-pointcloud-matching | ContrastiveLoss | false | 5,598 | [
"MIT"
] | 1 | cfe140f2be1110ed75b6edd27538021e513a31c9 | https://github.com/MinesNicaicai/large-scale-pointcloud-matching/tree/cfe140f2be1110ed75b6edd27538021e513a31c9 |
EncoderImageWeightNormPrecomp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from collections im... | sungjune-p/SCAN | EncoderImageWeightNormPrecomp | false | 10,820 | [
"Apache-2.0"
] | 0 | a3013944a05b48e952141fa295a8132d25da2e97 | https://github.com/sungjune-p/SCAN/tree/a3013944a05b48e952141fa295a8132d25da2e97 |
NSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Flash-Of-Thunder/testing | NSELoss | false | 8,097 | [
"Apache-2.0"
] | 18 | 36366e2cd32756fb07abc533ecbb7672a4738bc6 | https://github.com/Flash-Of-Thunder/testing/tree/36366e2cd32756fb07abc533ecbb7672a4738bc6 |
TwoLayerNet | import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
class TwoLayerNet(nn.Module):
def __init__(self, D_in: 'int', H: 'int', D_out: 'int') ->None:
"""
In the constructor we instantiate two nn.Linear modules and assign them as
member variables.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | JohnlNguyen/FLSim | TwoLayerNet | false | 13,904 | [
"BSD-3-Clause"
] | 79 | a5ed7c0b84499cd9dbc5fe95f8bcb4ba8ab5a5cb | https://github.com/JohnlNguyen/FLSim/tree/a5ed7c0b84499cd9dbc5fe95f8bcb4ba8ab5a5cb |
BridgeConnection | import torch
import torch.nn as nn
from torch.utils import tensorboard as tensorboard
class BridgeConnection(nn.Module):
def __init__(self, in_dim, out_dim, dout_p):
super(BridgeConnection, self).__init__()
self.norm = nn.LayerNorm(in_dim)
self.linear = nn.Linear(in_dim, out_dim)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Harbar-Inbound/BMT | BridgeConnection | false | 11,861 | [
"MIT"
] | 0 | ec8826f0633db754c7ea8d206672aa0b6b6048fd | https://github.com/Harbar-Inbound/BMT/tree/ec8826f0633db754c7ea8d206672aa0b6b6048fd |
AvgConsensus | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._emp... | HypnosXC/mmaction2 | AvgConsensus | false | 13,816 | [
"Apache-2.0"
] | 549 | a26d5f981449445a5e22a0a60d8b285e06c3dd6e | https://github.com/HypnosXC/mmaction2/tree/a26d5f981449445a5e22a0a60d8b285e06c3dd6e |
TorchFlattenNet | import torch
class TorchFlattenNet(torch.nn.Module):
def __init__(self):
super(TorchFlattenNet, self).__init__()
self.conv1 = torch.nn.Conv2d(1, 32, 3, 1)
def forward(self, x):
x = self.conv1(x)
return torch.flatten(x, 1)
def get_inputs():
return [torch.rand([4, 1, 64, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
reinterpret_tens... | TomokiHirose/convert_diff_fw_params | TorchFlattenNet | false | 2,934 | [
"MIT"
] | 0 | ba574ea52ae5574c9fbaabd340b8ccd0bf9ab5c5 | https://github.com/TomokiHirose/convert_diff_fw_params/tree/ba574ea52ae5574c9fbaabd340b8ccd0bf9ab5c5 |
GeM | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch._utils
import torch.optim
class GeM(nn.Module):
def __init__(self, p=3):
super(GeM, self).__init__()
self.p = p
self.eps = 1e-06
def forward(self, x):
return self.gem(x, p... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | Alicegaz/torchok | GeM | false | 16,928 | [
"Apache-2.0"
] | 8 | 7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 | https://github.com/Alicegaz/torchok/tree/7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 |
PositionMSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | vegetablejuiceftw/soft-pointer-networks | PositionMSELoss | false | 11,073 | [
"MIT"
] | 0 | 9705d9688b6b69db3948172771df4c367165c948 | https://github.com/vegetablejuiceftw/soft-pointer-networks/tree/9705d9688b6b69db3948172771df4c367165c948 |
ColumnMaxPooling | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.optim
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.ass... | MauTrib/gnn-en-folie | ColumnMaxPooling | false | 821 | [
"Apache-2.0"
] | 0 | 3ca639919a2b285a41641717f4131107c015b510 | https://github.com/MauTrib/gnn-en-folie/tree/3ca639919a2b285a41641717f4131107c015b510 |
ShuffleCatAlt | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | jjkennedy3/PINTO_model_zoo | ShuffleCatAlt | false | 6,959 | [
"MIT"
] | 1 | a181c3015a6241873798c4ad3eadd4ce97024f70 | https://github.com/jjkennedy3/PINTO_model_zoo/tree/a181c3015a6241873798c4ad3eadd4ce97024f70 |
TokenEmbedding | import math
import torch
from torch import Tensor
import torch.nn as nn
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import torch.nn
import torch.optim
import torch.profiler
class TokenEmbedding(nn.Module):
def __init__(self, vocab_size: 'int', emb_... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import to... | Nayef211/tutorials | TokenEmbedding | false | 9,540 | [
"BSD-3-Clause"
] | 0 | faf2c476fc3be855051fbea3cce77eaf7b2a2175 | https://github.com/Nayef211/tutorials/tree/faf2c476fc3be855051fbea3cce77eaf7b2a2175 |
CausalAttentionSortNet | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | tatp22/sinkhorn-transformer | CausalAttentionSortNet | false | 13,040 | [
"MIT"
] | 0 | 3eaa76e99efeee75cf8298defaaef51621c55ff4 | https://github.com/tatp22/sinkhorn-transformer/tree/3eaa76e99efeee75cf8298defaaef51621c55ff4 |
ClassifierDummy | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Omkar-Ranadive/Fine-Tuning-BERT | ClassifierDummy | false | 5,698 | [
"Apache-2.0"
] | 1 | b046092ec4007a4a59e1a478576cca7557c18d76 | https://github.com/Omkar-Ranadive/Fine-Tuning-BERT/tree/b046092ec4007a4a59e1a478576cca7557c18d76 |
EdgeGCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn... | hou-yz/pygcn | EdgeGCN | false | 3,629 | [
"MIT"
] | 0 | 26195954035c5eaae2d6e086cfec24cad2642f2e | https://github.com/hou-yz/pygcn/tree/26195954035c5eaae2d6e086cfec24cad2642f2e |
PatchMerging3D | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
class PatchMerging3D(nn.Module):
""" Patch Merging Layer
Args:
dim (int): Number of input channels.
norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | HarshSulakhe/pytorch_connectomics | PatchMerging3D | false | 9,862 | [
"MIT"
] | 0 | 73402e654afde69a43a5836cc90a32ef75c75dc2 | https://github.com/HarshSulakhe/pytorch_connectomics/tree/73402e654afde69a43a5836cc90a32ef75c75dc2 |
FocalLossSigmoid | import torch
import torch.nn as nn
from math import sqrt as sqrt
from itertools import product as product
class FocalLossSigmoid(nn.Module):
"""
sigmoid version focal loss
"""
def __init__(self, alpha=0.25, gamma=2, size_average=False):
super(FocalLossSigmoid, self).__init__()
self.al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | wangbingok1118/SSD_Pytorch | FocalLossSigmoid | false | 4,516 | [
"MIT"
] | 0 | 8d3f924671cec367c3c420eba2f002cc5b5181bb | https://github.com/wangbingok1118/SSD_Pytorch/tree/8d3f924671cec367c3c420eba2f002cc5b5181bb |
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